We automatically create enormous, free and multilingual silver-standard training annotations
for named entity recognition (ner) by exploiting the text and structure of Wikipedia. Most ner …

We study a comprehensive set of features used in supervised named entity recognition. We
explore various combinations of features and compare their impact on recognition …

Fine-grained entity typing (FGET) is an important natural language processing (NLP) task. It
is to assign fine-grained semantic types of a type taxonomy (eg, Person/artist/actor) to entity …

Automatic methods to create entity dictionaries or gazetteers have used only a small number
of entity types (18 at maximum), which could pose a limitation for fine-grained information …

Given the sheer amount of work and expertise required in authoring Wikipedia articles,
automatic tools that help Wikipedia contributors in generating and improving content are …

维基百科实体分类对自然语言处理和机器学习具有重要的作用. 本文采用机器学习的方法对中文
维基百科的条目进行实体分类, 在利用维基百科页面中半结构化信息和无结构化文本作为基本 …

This thesis addresses the problem of fine-grained NER for Arabic, which poses unique
linguistic challenges to NER; such as the absence of capitalisation and short vowels, the …

El presente artículo realiza una revisión del tema, representación y clasificación de de
relaciones de pertenencia entre los nodos de una red social. Para ello, se abordan …

We propose a domain adaptation method for supervised named entity recognition (NER).
Our NER uses conditional random fields and we rank and filter out features of a new …

El presente artículo realiza una revisión del tema, representación y clasificación de de
relaciones de pertenencia entre los nodos de una red social. Para ello, se abordan …